{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--BOOK_INFORMATION-->\n",
    "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PHydro-cover-small.png\">\n",
    "*This is the Jupyter notebook version of the [Python in Hydrology](http://www.greenteapress.com/pythonhydro/pythonhydro.html) by Sat Kumar Tomer.*\n",
    "*Source code is available at [code.google.com](https://code.google.com/archive/p/python-in-hydrology/source).*\n",
    "\n",
    "*The book is available under the [GNU Free Documentation License](http://www.gnu.org/copyleft/fdl.html). If you have comments, corrections or suggestions, please send email to satkumartomer@gmail.com.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Rainfall](04.04-Rainfall.ipynb) | [Contents](Index.ipynb) | [Inﬁltration](04.06-Inﬁltration.ipynb) >"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.5 蒸发\n",
    "\n",
    "根据能量平衡，忽略感热通量和地热通量后，蒸发率($E_r$)可以计算为，\n",
    "\n",
    "<center>$E_r=\\frac{R_n}{l_v\\rho_w}$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.3)</center>\n",
    "\n",
    "其中，$R_n$是净辐射，$l_v$是净汽化潜热，$\\rho_w$是水的密度。$l_v$可以近似为，\n",
    "\n",
    "<center>$l_v=2500-2.36×T$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.4)</center>\n",
    "\n",
    "其中，$T$是摄氏度。\n",
    "\n",
    "根据空气动力学，蒸发率（$E_a$）可以计算为，\n",
    "\n",
    "<center>$E_a=B(e_{as}-e_a)$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.5)</center>\n",
    "\n",
    "其中，\n",
    "\n",
    "<center>$B=\\frac{0.622k^2\\rho_au_2}{p\\rho_w[ln(z_2/z_0)]^2}$&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.6)</center>\n",
    "\n",
    "$e_{as}$为饱和蒸气压，$e_a$是蒸气压，$k$是冯卡曼系数,$u_2$是在$z_2$米高度测量的风速，$p$是空气压力，$z_0$是粗糙度高度。\n",
    "\n",
    "通常，通过结合能量平衡和空气动力学方法计算蒸发量。在这种情况下，$E$变为，\n",
    "\n",
    "<center>$E=\\frac{\\Delta}{\\Delta+\\gamma}E_r+\\frac{\\gamma}{\\Delta+\\gamma}E_a$&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.7)</center>\n",
    "\n",
    "其中，$\\Delta$是饱和蒸汽压力曲线的梯度，\n",
    "\n",
    "<center>$\\Delta=\\frac{4098e_s}{(273.3+T)^2}$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.8)</center>\n",
    "\n",
    "$\\gamma$是湿度常数，被定义为，\n",
    "\n",
    "<center>$\\gamma=\\frac{C_pK_hp}{0.622l_vK_w}$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.9)</center>\n",
    "\n",
    "$k_h$和$k_w$分别是热量和蒸汽扩散率。\n",
    "\n",
    "让我们使用随机数生成模拟数据。我们知道`np.random.rand`在`[0，1]`区间内提供均匀分布的随机数。如果我们想在其他的范围内得到均匀分布的随机数，例如`[a,b]`，我们可以用下面的方式来转换变量:\n",
    "\n",
    "<center>$x_{new}=a+(b-a)*x_{old}$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.10)</center>\n",
    "\n",
    "其中，$x_{old}$是`[0,1]`上的均匀随机变量，$x_{new}$有`[a,b]`的范围。`np.random.randn`提供均值为0，标准差为1的正态分布的随机变量。如果我们对平均值为$\\mu$，标准差为$\\gamma$的正态分布随机变量感兴趣，我们做下面的转换。\n",
    "\n",
    "<center>$y_{new}=μ+\\sigma*y_{old}$,&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(4.11)</center>\n",
    "\n",
    "其中，$y_{new}$是均值为$\\mu$且标准差为$\\sigma$的变换通量，$y_{old}$是由`np.random.randn`函数产生的具有均值为0且标准差为1的正态分布随机变量。\n",
    "\n",
    "在下面的例子中，我们将生成通常范围内的变量。变量之后的注释提供了在均匀分布随机变量情况下的上下限，以及在变量为正态分布时的均值和标准差的细节。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from __future__ import division\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 生成模拟数据\n",
    "Rn = 150+100*np.random.rand(100) # 下限= 150, 上限 = 250\n",
    "T = 25+3*np.random.randn(100) # 均值 = 25, 标准差 = 3\n",
    "Rh = 0.2+0.6*np.random.rand(100) # 下限 = 0.2, 上限 = 0.8\n",
    "u2 = 3+np.random.randn(100) # 均值 = 3, 标准差 = 1\n",
    "\n",
    "# 定义常量\n",
    "rho_w = 997; rho_a = 1.19; p = 101.1e3; z2 = 2\n",
    "z0 = 0.03e-2; k = 0.4; Cp = 1005"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在，我们采用基于能量平衡的方法来估算蒸发量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lv = (2500-2.36*T)*1000 # 乘以1000将KJ/kg转换为J/kg\n",
    "Er = 200/(lv*997)\n",
    "Er *= 1000*86400 # 将 m/s 转换为 mm/day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们使用乘法和赋值运算符来转换单位。我们也可以通过简单的乘法来完成，即$E_r = E_r*1000*86400$。乘法和赋值运算速度很快，因为它不会在内存中创建任何临时变量。事实上，所有的赋值操作符都比简单操作符快，只要有作用域就可以使用。现在我们用空气动力学方法估算蒸发量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "B = 0.622*k**2*rho_a*u2/(p*rho_w*(np.log(z2/z0))**2)\n",
    "e_s = 611*np.exp(17.27*T/(237.3+T))\n",
    "e_a = Rh*e_s\n",
    "Ea = B*(e_s-e_a)\n",
    "Ea *= 1000*86400 # 将 m/s 转换为 mm/day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将能量平衡和空气动力学方法相结合，对蒸发量进行改进。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gamma = Cp*p/(0.622*lv) # 由于 kh/kw = 1, 因而他们被抵消了\n",
    "delta = 4098*e_s/(237.3+T)**2\n",
    "w = delta/(delta+gamma)\n",
    "E = w*Er + (1-w)*Ea"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在，我们得到了四个重要的变量:能量平衡法得到蒸发量($E_r$)、空气动力学方法得到的蒸发量($E_a$)、组合蒸发量($E$)、能量平衡法蒸发比法($E_r/E$)。我们可以将这四个变量绘制在四个不同的图中，也可以将图形分成四个部分。`subplot`是使图分段的一种函数。`subplot`的第一个参数是所需的行数，第二个参数是理想的图形列数，第三个参数是`subplot`中的位置，这是从左到右，从上到下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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uiAavUgyTCR0DHUGX1PH2HUNF3+ulU746Og9ZIniDk4i32YlwYjJXPGPAsKhL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tFK0SJJLcOH0XAO29enCj83lDFluDBY107vtcZYbppbdt7NtdseWPJ3t+YTSXql5bQH9WEME8bC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x59a3d6fc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "plt.subplot(2,2,1)\n",
    "plt.plot(Er)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Er')\n",
    "\n",
    "plt.subplot(2,2,2)\n",
    "plt.plot(Ea)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Ea')\n",
    "\n",
    "plt.subplot(2,2,3, facecolor ='y')\n",
    "plt.plot(E)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('E')\n",
    "\n",
    "plt.subplot(2,2,4, facecolor ='g')\n",
    "plt.plot(w)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Er/E')\n",
    "plt.savefig('figures/E.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>图4.7:$E_r,E_a,E$和$E_r/E$的估值</center>\n",
    "\n",
    "$E_r,E_a,E$和$E_r/E$的估值如图4.7所示。我们还是用`facecolor`定义`subplot`的背景颜色。\n",
    "\n",
    "在图4.7中，子图4的`ylabel`与子图3重叠。这可以通过改变`wspace`校正。下面将对此进行说明。图4.8给出了改进的情节。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x59a66b9668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QVUI2oQrXTBhGJTdRWlfRl9GxdTAr6GmpYvsSGkumhbE5h31sdo1bV1IDJzY8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\nsLDoGNZoWFhYWFh0DGs0LCwsLCw6xv8Hgo/8JcEw8mQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x59a66b9518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.clf()\n",
    "fig = plt.figure()\n",
    "fig.subplots_adjust(wspace=0.6)\n",
    "plt.subplot(2,2,1)\n",
    "plt.plot(Er)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Er')\n",
    "\n",
    "plt.subplot(2,2,2)\n",
    "plt.plot(Ea)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Ea')\n",
    "\n",
    "plt.subplot(2,2,3, facecolor='y')\n",
    "plt.plot(E)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('E')\n",
    "\n",
    "plt.subplot(2,2,4, facecolor='g')\n",
    "plt.plot(w)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Er/E')\n",
    "plt.savefig('figures/corr_E.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>图4.8:校正ylabel$后E_r,E_a,E$和$E_r/E$的估值</center>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
